Fraud News Network Launches AI Investment Risk Scoring Tool
Barry Minkow has launched Fraud News Network, a free app that combines fraud news, original investigations, and an AI investment risk scoring tool, announced in a press release.
The tool is built on Genspark and lets users upload private placement memorandums, pitch decks, offering summaries, or investment solicitations. It returns a risk score from 1 to 10 in minutes, with 10 listed as the best score.
The AI analysis flags items such as guaranteed returns, undisclosed conflicts, unsupported valuations, pressure tactics, and structural issues. The release says the methodology is based on patterns from 13 fraudulent schemes that regulators later shut down.
Fraud News Network said the scoring tool currently focuses on debt funds, income funds, multifamily offerings, and self storage offerings. Basic scoring is free, while deeper reviews with title reports and other verification are offered for a fee.
We hope you enjoyed this article.
Consider subscribing to one of our newsletters like Finance AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from: Finance
Subscribe to Finance AI Weekly
Weekly newsletter about AI in finance. Covers AI-driven trading, fintech innovations, and data analytics transforming markets
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read more